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Generic and efficient framework for search trees on flash memory storage systems / Mohamed Sarwat in Geoinformatica, vol 17 n° 3 (July 2013)  

Public [article]  inGeoinformatica > vol 17 n° 3 (July 2013) . - pp 489 - 519 Titre : Generic and efficient framework for search trees on flash memory storage systems Type de document : Article/Communication Auteurs : Mohamed Sarwat, Auteur ; Mohamed F. Mokbel, Auteur ; Xun Zhou, Auteur ; Suman Nath, Auteur Année de publication : 2013 Article en page(s) : pp 489 - 519 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Informatique [Termes IGN] arbre (mathématique) [Termes IGN] arbre-R [Termes IGN] indexation spatiale [Termes IGN] mémoire d'ordinateur [Termes IGN] mémoire flash Résumé : (Auteur) Tree index structures are crucial components in data management systems. Existing tree index structure are designed with the implicit assumption that the underlying external memory storage is the conventional magnetic hard disk drives. This assumption is going to be invalid soon, as flash memory storage is increasingly adopted as the main storage media in mobile devices, digital cameras, embedded sensors, and notebooks. Though it is direct and simple to port existing tree index structures on the flash memory storage, that direct approach does not consider the unique characteristics of flash memory, i.e., slow write operations, and erase-before-update property, which would result in a sub optimal performance. In this paper, we introduce FAST (i.e., Flash-Aware Search Trees) as a generic framework for flash-aware tree index structures. FAST distinguishes itself from all previous attempts of flash memory indexing in two aspects: (1) FAST is a generic framework that can be applied to a wide class of data partitioning tree structures including R-tree and its variants, and (2) FAST achieves both efficiency and durability of read and write flash operations through memory flushing and crash recovery techniques. Extensive experimental results, based on an actual implementation of FAST inside the GiST index structure in PostgreSQL, show that FAST achieves better performance than its competitors. Numéro de notice : A2013-381 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Article DOI : 10.1007/s10707-012-0164-9 Date de publication en ligne : 30/08/2012 En ligne : https://doi.org/10.1007/s10707-012-0164-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32519 [article]

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Spatial inverse query processing / Thomas Bernecker in Geoinformatica, vol 17 n° 3 (July 2013)  

Public [article]  inGeoinformatica > vol 17 n° 3 (July 2013) . - pp 449 - 487 Titre : Spatial inverse query processing Type de document : Article/Communication Auteurs : Thomas Bernecker, Auteur ; Tobias Emrich, Auteur ; Hans-Peter Kriegel, Auteur ; Nikos Mamoulis, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 449 - 487 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] plus proche voisin, algorithme du [Termes IGN] requête spatiale [Termes IGN] requête spatiale inverse Résumé : (Auteur) Traditional spatial queries return, for a given query object q, all database objects that satisfy a given predicate, such as epsilon range and k-nearest neighbors. This paper defines and studies inverse spatial queries, which, given a subset of database objects Q and a query predicate, return all objects which, if used as query objects with the predicate, contain Q in their result. We first show a straightforward solution for answering inverse spatial queries for any query predicate. Then, we propose a filter-and-refinement framework that can be used to improve efficiency. We show how to apply this framework on a variety of inverse queries, using appropriate space pruning strategies. In particular, we propose solutions for inverse epsilon range queries, inverse k-nearest neighbor queries, and inverse skyline queries. Furthermore, we show how to relax the definition of inverse queries in order to ensure non-empty result sets. Our experiments show that our framework is significantly more efficient than naive approaches. Numéro de notice : A2013-382 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-012-0162-y Date de publication en ligne : 24/08/2012 En ligne : https://doi.org/10.1007/s10707-012-0162-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32520 [article]

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Index-based query processing on distributed multidimensional data / George Tsatsanifos in Geoinformatica, vol 17 n° 3 (July 2013)  

Public [article]  inGeoinformatica > vol 17 n° 3 (July 2013) . - pp 489 - 519 Titre : Index-based query processing on distributed multidimensional data Type de document : Article/Communication Auteurs : George Tsatsanifos, Auteur ; Dimitri Sacharidis, Auteur ; Timos Sellis, Auteur Année de publication : 2013 Article en page(s) : pp 489 - 519 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] base de données répartie [Termes IGN] données multidimensionnelles [Termes IGN] index spatial [Termes IGN] requête spatiale Résumé : (Auteur) This work introduces decentralized query processing techniques based on MIDAS, a novel distributed multidimensional index. In particular, MIDAS implements a distributed k-d tree, where leaves correspond to peers, and internal nodes dictate message routing. MIDAS requires that peers maintain little network information, and features mechanisms that support fault tolerance and load balancing. The proposed algorithms process point and range queries over the multidimensional indexed space in only O(log n) hops in expectance, where n is the network size. For nearest neighbor queries, two processing alternatives are discussed. The first, termed eager processing, has low latency (expected value of O(log n) hops) but may involve a large number of peers. The second, termed iterative processing, has higher latency (expected value of O(log2 n) hops) but involves far fewer peers. A detailed experimental evaluation demonstrates that our query processing techniques outperform existing methods for settings involving real spatial data as well as in the case of high dimensional synthetic data. Numéro de notice : A2013-383 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1007/s10707-012-0163-x Date de publication en ligne : 09/08/2012 En ligne : https://doi.org/10.1007/s10707-012-0163-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32521 [article]

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